{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签\n",
    "plt.rcParams['axes.unicode_minus'] = False  # 用来正常显示负号"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 简单柱状图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<BarContainer object of 5 artists>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = ['语文','数学','英语','Python','化学']\n",
    "y = [20,10,40,60,10]\n",
    "\n",
    "plt.figure(figsize=(5,3))\n",
    "plt.bar(x, y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Pandas获取Excel数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>年份</th>\n",
       "      <th>销售额</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2014</td>\n",
       "      <td>1962035</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2015</td>\n",
       "      <td>2838693</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016</td>\n",
       "      <td>2317447</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2017</td>\n",
       "      <td>2335002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018</td>\n",
       "      <td>2438570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2019</td>\n",
       "      <td>1675591</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2020</td>\n",
       "      <td>3568120</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     年份      销售额\n",
       "0  2014  1962035\n",
       "1  2015  2838693\n",
       "2  2016  2317447\n",
       "3  2017  2335002\n",
       "4  2018  2438570\n",
       "5  2019  1675591\n",
       "6  2020  3568120"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_excel('./data/plot.xlsx', sheet_name='bar1')\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "x, y = df.年份, df.销售额"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(5,3))\n",
    "plt.title('年销售额')\n",
    "plt.xlabel('年份')\n",
    "plt.ylabel('销售额')\n",
    "\n",
    "plt.bar(x,y, width=0.6)\n",
    "\n",
    "# 在每个柱子上显示数值\n",
    "for a,b in zip(x,y):\n",
    "    plt.text(a, b, '{:.1f}万'.format(b/10000), ha='center', va= 'bottom', fontsize=10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 一次绘制多个柱状图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>年份</th>\n",
       "      <th>北区</th>\n",
       "      <th>中区</th>\n",
       "      <th>南区</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2014</td>\n",
       "      <td>634704</td>\n",
       "      <td>534917</td>\n",
       "      <td>792414</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2015</td>\n",
       "      <td>1218844</td>\n",
       "      <td>746554</td>\n",
       "      <td>873295</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016</td>\n",
       "      <td>1013322</td>\n",
       "      <td>904058</td>\n",
       "      <td>400067</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2017</td>\n",
       "      <td>1068521</td>\n",
       "      <td>12269</td>\n",
       "      <td>1254212</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018</td>\n",
       "      <td>419352</td>\n",
       "      <td>526985</td>\n",
       "      <td>1492233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2019</td>\n",
       "      <td>1190076</td>\n",
       "      <td>117510</td>\n",
       "      <td>368005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2020</td>\n",
       "      <td>695421</td>\n",
       "      <td>1433961</td>\n",
       "      <td>1438738</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     年份       北区       中区       南区\n",
       "0  2014   634704   534917   792414\n",
       "1  2015  1218844   746554   873295\n",
       "2  2016  1013322   904058   400067\n",
       "3  2017  1068521    12269  1254212\n",
       "4  2018   419352   526985  1492233\n",
       "5  2019  1190076   117510   368005\n",
       "6  2020   695421  1433961  1438738"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2 = pd.read_excel('data/plot.xlsx', sheet_name='bar2')\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "x, y1, y2, y3 = df2.年份, df2.北区, df2.中区, df2.南区"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 蔟形柱状图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x249cf541390>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(5,3))\n",
    "plt.title('年销售额')\n",
    "plt.xlabel('年份')\n",
    "plt.ylabel('地区')\n",
    "\n",
    "w=0.2\n",
    "plt.bar(x-w,y1, width=w, label='北区')\n",
    "plt.bar(x,y2, width=w, label='中区')\n",
    "plt.bar(x+w,y3, width=w, label='南区')\n",
    "\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 堆叠柱状图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x249d0e62aa0>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(5,3))\n",
    "plt.title('年销售额')\n",
    "plt.xlabel('年份')\n",
    "plt.ylabel('地区')\n",
    "\n",
    "plt.bar(x,y1, label='北区')\n",
    "plt.bar(x,y2, label='中区', bottom=y1)\n",
    "plt.bar(x,y3, label='南区', bottom=y1+y2)\n",
    "\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 条形图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<BarContainer object of 7 artists>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.barh(x, y1)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": ".venv",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
